HIV-1 coreceptor usage prediction without multiple alignments: an application of string kernels.
about
Hybrid approach for predicting coreceptor used by HIV-1 from its V3 loop amino acid sequenceClinical significance of HIV-1 coreceptor usage.Hierarchical classification of protein folds using a novel ensemble classifierReliable genotypic tropism tests for the major HIV-1 subtypesHIV-1 envelope subregion length variation during disease progressionMachine learning on normalized protein sequences.Comparative determination of HIV-1 co-receptor tropism by Enhanced Sensitivity Trofile, gp120 V3-loop RNA and DNA genotypingCo-receptor tropism prediction among 1045 Indian HIV-1 subtype C sequences: Therapeutic implications for India.POPISK: T-cell reactivity prediction using support vector machines and string kernels.HIV coreceptor tropism determination and mutational pattern identification.Profile of HIV type 1 coreceptor tropism among Kenyan patients from 2009 to 2010Comparative analysis of cell culture and prediction algorithms for phenotyping of genetically diverse HIV-1 strains from Cameroon.Performance of commonly used genotypic assays and comparison with phenotypic assays of HIV-1 coreceptor tropism in acutely HIV-1-infected patients.Recovery of replication-competent residual HIV-1 from plasma of a patient receiving prolonged, suppressive highly active antiretroviral therapy
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P2860
HIV-1 coreceptor usage prediction without multiple alignments: an application of string kernels.
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on 04 December 2008
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
HIV-1 coreceptor usage predict ...... application of string kernels.
@en
HIV-1 coreceptor usage predict ...... application of string kernels.
@nl
type
label
HIV-1 coreceptor usage predict ...... application of string kernels.
@en
HIV-1 coreceptor usage predict ...... application of string kernels.
@nl
prefLabel
HIV-1 coreceptor usage predict ...... application of string kernels.
@en
HIV-1 coreceptor usage predict ...... application of string kernels.
@nl
P2093
P2860
P356
P1433
P1476
HIV-1 coreceptor usage predict ...... application of string kernels.
@en
P2093
François Laviolette
Jacques Corbeil
Sébastien Boisvert
P2860
P2888
P356
10.1186/1742-4690-5-110
P577
2008-12-04T00:00:00Z
P5875
P6179
1046301375